import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import plotly.express as px
data=pd.read_csv('C:/Users/Rakesh/Datasets/unemployment.csv')
data.head()
| Region | Date | Frequency | Estimated Unemployment Rate (%) | Estimated Employed | Estimated Labour Participation Rate (%) | Region.1 | longitude | latitude | |
|---|---|---|---|---|---|---|---|---|---|
| 0 | Andhra Pradesh | 31-01-2020 | M | 5.48 | 16635535 | 41.02 | South | 15.9129 | 79.74 |
| 1 | Andhra Pradesh | 29-02-2020 | M | 5.83 | 16545652 | 40.90 | South | 15.9129 | 79.74 |
| 2 | Andhra Pradesh | 31-03-2020 | M | 5.79 | 15881197 | 39.18 | South | 15.9129 | 79.74 |
| 3 | Andhra Pradesh | 30-04-2020 | M | 20.51 | 11336911 | 33.10 | South | 15.9129 | 79.74 |
| 4 | Andhra Pradesh | 31-05-2020 | M | 17.43 | 12988845 | 36.46 | South | 15.9129 | 79.74 |
data.columns=['States','Date','Frequency','Estimated Unemployment Rate','Estimated Employed','Estimated Labour Participation Rate','Region','longitude','latitude']
data.head()
| States | Date | Frequency | Estimated Unemployment Rate | Estimated Employed | Estimated Labour Participation Rate | Region | longitude | latitude | |
|---|---|---|---|---|---|---|---|---|---|
| 0 | Andhra Pradesh | 31-01-2020 | M | 5.48 | 16635535 | 41.02 | South | 15.9129 | 79.74 |
| 1 | Andhra Pradesh | 29-02-2020 | M | 5.83 | 16545652 | 40.90 | South | 15.9129 | 79.74 |
| 2 | Andhra Pradesh | 31-03-2020 | M | 5.79 | 15881197 | 39.18 | South | 15.9129 | 79.74 |
| 3 | Andhra Pradesh | 30-04-2020 | M | 20.51 | 11336911 | 33.10 | South | 15.9129 | 79.74 |
| 4 | Andhra Pradesh | 31-05-2020 | M | 17.43 | 12988845 | 36.46 | South | 15.9129 | 79.74 |
plt.style.use('seaborn-whitegrid')
plt.figure(figsize=(12,10))
sns.heatmap(data.corr())
plt.show()
data.columns= ["States","Date","Frequency",
"Estimated Unemployment Rate","Estimated Employed",
"Estimated Labour Participation Rate","Region",
"longitude","latitude"]
plt.title('Indian Unemployment')
sns.histplot(x='Estimated Employed', hue='Region', data=data)
plt.show()
plt.title("Indian Unemployment")
sns.histplot(x="Estimated Unemployment Rate", hue="Region", data=data)
plt.show()
unemployment=data[['States','Region','Estimated Unemployment Rate']]
figure=px.sunburst(unemployment,path=['Region','States'], values='Estimated Unemployment Rate', width=700, height=700, color_continuous_scale='RdY1Gn',title='Unemployment Rate In India')
figure.show()
C:\Users\Rakesh\Downloads\Anaconda\lib\site-packages\plotly\express\_core.py:1637: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead. df_all_trees = df_all_trees.append(df_tree, ignore_index=True) C:\Users\Rakesh\Downloads\Anaconda\lib\site-packages\plotly\express\_core.py:1637: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead. df_all_trees = df_all_trees.append(df_tree, ignore_index=True)